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Reseach Article

An Approach based on Run Length Count for Denoising the Kannada Characters

by Karthik S, Mamatha H.r, Srikanta Murthy K
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 50 - Number 18
Year of Publication: 2012
Authors: Karthik S, Mamatha H.r, Srikanta Murthy K
10.5120/7875-1192

Karthik S, Mamatha H.r, Srikanta Murthy K . An Approach based on Run Length Count for Denoising the Kannada Characters. International Journal of Computer Applications. 50, 18 ( July 2012), 42-46. DOI=10.5120/7875-1192

@article{ 10.5120/7875-1192,
author = { Karthik S, Mamatha H.r, Srikanta Murthy K },
title = { An Approach based on Run Length Count for Denoising the Kannada Characters },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 50 },
number = { 18 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 42-46 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume50/number18/7875-1192/ },
doi = { 10.5120/7875-1192 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:48:41.813986+05:30
%A Karthik S
%A Mamatha H.r
%A Srikanta Murthy K
%T An Approach based on Run Length Count for Denoising the Kannada Characters
%J International Journal of Computer Applications
%@ 0975-8887
%V 50
%N 18
%P 42-46
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Optical Character Recognition (OCR) is one of the important fields in image processing and pattern recognition domain. OCR with high accuracy finds application in offices, banks, healthcare etc. The accuracy of the OCR is primarily dependent on the quality of the input image. So, to achieve high accuracy OCR we should provide a high quality image, which is free from different types of noises, degradation, skews etc. In this paper, we have made an attempt to remove the noise, which is present in the input image. A novel method based on run length count is proposed to denoise the images. In this approach first the noisy image is binarized. Based on the horizontal and vertical run length count, the noise in the image will be identified and eliminated. The algorithm is tested with noisy epigraphical document images, noisy printed document images. The effectiveness of the algorithm is verified with images having synthetic noise derived from Gaussian, Speckle and Poisson noise models. The experimental results show that the proposed method is efficient for noise elimination.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Optical Character Recognition Image Denoising Run Length Count Epigraphical Document Printed Document Gaussian Noise Speckle Noise Poisson Noise